Instructor: Ernest Fraenkel

This lecture on predicting protein structure covers refining a partially correct structure. Methods include energy minimization, molecular dynamics, and simulated annealing. He moves on to methods for predicting structure from a sequence of amino acid.

1. Introduction to Computational and Systems Biology
2. Local Alignment (BLAST) and Statistics
3. Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)
4. Comparative Genomic Analysis of Gene Regulation
5. Library Complexity and Short Read Alignment (Mapping)
6. Genome Assembly
7. ChIP-seq Analysis; DNA-protein Interactions
8. RNA-sequence Analysis: Expression, Isoforms
9. Modeling and Discovery of Sequence Motifs
10. Markov and Hidden Markov Models of Genomic and Protein Features
11. RNA Secondary Structure; Biological Functions and Predictions
12. Introduction to Protein Structure; Structure Comparison and Classification
13. Predicting Protein Structure
14. Predicting Protein Interactions
15. Gene Regulatory Networks
16. Protein Interaction Networks
17. Logic Modeling of Cell Signaling Networks
18. Analysis of Chromatin Structure
19. Discovering Quantitative Trait Loci (QTLs)
20. Human Genetics, SNPs, and Genome Wide Associate Studies
21. Synthetic Biology: From Parts to Modules to Therapeutic Systems
22. Causality, Natural Computing, and Engineering Genomes

This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas. This course is designed for advanced undergraduates and graduate students with strong backgrounds in either molecular biology or computer science, but not necessarily both. The scripting language Python—which is widely used for bioinformatics and computational biology—will be used; foundational material covering basic programming skills will be provided by the teaching assistants. Graduate versions of the course involve an additional project component.

Instructors: Christopher Burge, David Gifford, Ernest Fraenkel